If you’re looking for ready-to-use scripts to automate the conversion, check the accompanying GitHub repository (link below) for a msor_to_sor.py tool that scans your MSOR implementation and suggests an equivalent SOR parameter. Have you successfully converted MSOR to SOR in your project? Share your experience and the omega values you used in the comments below.
In such cases, the conversion is not a simple parameter substitution. You must reformulate the problem using or switch to a different splitting (e.g., SSOR – Symmetric SOR). Part 5: Common Pitfalls When You Convert MSOR to SOR Avoid these mistakes during your conversion: convert msor to sor
omega = 1.5 # Single global parameter This is the non-trivial case. If your MSOR uses ( \omega_1 \neq \omega_2 ), you cannot simply pick one. You must find a single ( \omega_SOR ) that mimics the average behavior of MSOR. If you’re looking for ready-to-use scripts to automate
if (i is in Group 1): omega = 1.5 else: omega = 1.5 In such cases, the conversion is not a
(derived from the eigenvalues of the Jacobi matrix).